WASHINGTON — Two conventional machine learning algorithms and two convolutional neural network models achieved high glaucoma diagnostic performances by reading full retinal nerve fiber layer thickness maps, according to a speaker here.
“All four machine learning models had [areas under the curve] of greater than 0.90, and they significantly outperformed mean circumpapillary RNFL thickness, which had an AUC of 0.76,” Grace Richter, MD, MPH, said at the American Glaucoma Society annual meeting.
Richter and colleagues assessed the diagnostic accuracy of multiple machine learning
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